Sample Path for Intelligent Systems Specialization

The goal of this specialization is to balance programming skills and mathematical and statistical knowledge for AI and machine learning. Both skills are important for AI and machine learning in the real world.

The proposed math and statistics classes are towards the foundational theory skills; our general recommendation for additional courses not proposed in the sample path is to take more math and statistics classes.

The proposed programming classes (C291, C335) are towards becoming better low-level programmers; our general recommendation for additional courses towards foundational implementation skills is to learn more about numerical analysis and fast implementations. For additional courses outside the above sample path, we generally recommend more CS classes that improve your ability to write good code and collaborate on code with others.

The machine learning specific classes (B365, B363, B355, B490, B455) enable you to apply some of your foundational theory skills to algorithm development in machine learning and to apply your programming skills to real machine learning problems.

The more general agent-based classes (B351, B355) get you think more generally about decision-making and the design of intelligent agents. This sample path is intentionally challenging, to give the best preparation for work in industry or academia.